{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "import pickle\n",
    "from sklearn.metrics import confusion_matrix\n",
    "\n",
    "from tensorflow.keras.models import load_model\n",
    "\n",
    "from sklearn.metrics import accuracy_score, roc_curve, auc\n",
    "import seaborn as sns\n",
    "\n",
    "import copy"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "models = ['DetectNet','DNN', 'CNN', 'LSTM']\n",
    "_mods = ['BPSK', 'QPSK', '8PSK', 'PAM4', 'QAM16', 'QAM64', 'GFSK', 'CPFSK', ]\n",
    "sample_length = [64,128,256,512,1024]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "def radioml_IQ_data(filename, mod_name, _snr= -10, swap_dim = False):\n",
    "    '''\n",
    "        load dataset for single node model training\n",
    "    '''\n",
    "    snrs=\"\"\n",
    "    mods=\"\"\n",
    "    lbl =\"\"\n",
    "    Xd = pickle.load(open(filename,'rb'),encoding='latin')\n",
    "    snrs,mods = map(lambda j: sorted(list(set(map(lambda x: x[j], Xd.keys())))), [1,0])\n",
    "    X = []  \n",
    "    lbl = []\n",
    "    for mod in mods:\n",
    "        for snr in snrs:\n",
    "            if(snr == _snr):\n",
    "                X.append(Xd[(mod,snr)])\n",
    "                for i in range(Xd[(mod,snr)].shape[0]):  lbl.append((mod,snr))\n",
    "    X = np.vstack(X)\n",
    "    \n",
    "#     use QAM16 signal only\n",
    "    lbl = np.array(lbl) \n",
    "    index = np.where(lbl==mod_name)[0] \n",
    "    X = X[index]\n",
    "    lbl = lbl[index]\n",
    "    \n",
    "    maxlen = X.shape[-1]\n",
    "    SNR = []\n",
    "    for item in lbl:\n",
    "        SNR.append(item[-1])\n",
    "    SNR = np.array(SNR,dtype='int16')\n",
    "    \n",
    "    noise_vectors = []\n",
    "    for i in range(X.shape[0]):\n",
    "        real = np.random.randn(maxlen) \n",
    "        imag = np.random.randn(maxlen)\n",
    "        complex_noise_vector = real + 1j*imag\n",
    "        energy = np.sum(np.abs(complex_noise_vector)**2)\n",
    "        noise_vector = complex_noise_vector / (energy**0.5)\n",
    "        real = np.real(noise_vector)\n",
    "        imag = np.imag(noise_vector)\n",
    "        noise_vectors.append([real,imag])\n",
    "    noise_vectors = np.array(noise_vectors)   \n",
    "    \n",
    "    # one-hot label, [1,0] with signal, [0,1] noise only\n",
    "    dataset = np.concatenate((X,noise_vectors),axis=0)\n",
    "    labelset = np.concatenate(([[1,0]]*len(X),[[0,1]]*len(noise_vectors)),axis=0)\n",
    "    labelset = np.array(labelset,dtype='int16')\n",
    "    # use snr -100 to represent noise samples\n",
    "    SNR = np.concatenate((SNR,[-100]*len(noise_vectors)),axis=0) \n",
    "\n",
    "    total_num = len(dataset)\n",
    "    shuffle_idx = np.random.choice(range(0,total_num), size=total_num,replace=False)\n",
    "    \n",
    "    dataset = dataset[shuffle_idx]\n",
    "    labelset = labelset[shuffle_idx]\n",
    "    SNR = SNR[shuffle_idx]\n",
    "    \n",
    "    # split the whole dataset with ratio 3:1:1 into training, validation and testing set\n",
    "    train_num = int(total_num*0.6)\n",
    "    val_num = int(total_num*0.2)\n",
    "    \n",
    "    if(swap_dim):\n",
    "        dataset = np.einsum('ijk->ikj', dataset)\n",
    "\n",
    "    return dataset, labelset, SNR"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Varia modulação"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Loading  result/models/DetectNet/128/BPSKfinal.h5\n",
      "WARNING:tensorflow:Layer lstm will not use cuDNN kernel since it doesn't meet the cuDNN kernel criteria. It will use generic GPU kernel as fallback when running on GPU\n",
      "Loading  result/models/DetectNet/128/QPSKfinal.h5\n",
      "WARNING:tensorflow:Layer lstm will not use cuDNN kernel since it doesn't meet the cuDNN kernel criteria. It will use generic GPU kernel as fallback when running on GPU\n",
      "Loading  result/models/DetectNet/128/8PSKfinal.h5\n",
      "WARNING:tensorflow:Layer lstm will not use cuDNN kernel since it doesn't meet the cuDNN kernel criteria. It will use generic GPU kernel as fallback when running on GPU\n",
      "Loading  result/models/DetectNet/128/PAM4final.h5\n",
      "WARNING:tensorflow:Layer lstm will not use cuDNN kernel since it doesn't meet the cuDNN kernel criteria. It will use generic GPU kernel as fallback when running on GPU\n",
      "Loading  result/models/DetectNet/128/QAM16final.h5\n",
      "WARNING:tensorflow:Layer lstm will not use cuDNN kernel since it doesn't meet the cuDNN kernel criteria. It will use generic GPU kernel as fallback when running on GPU\n",
      "Loading  result/models/DetectNet/128/QAM64final.h5\n",
      "WARNING:tensorflow:Layer lstm will not use cuDNN kernel since it doesn't meet the cuDNN kernel criteria. It will use generic GPU kernel as fallback when running on GPU\n",
      "Loading  result/models/DetectNet/128/GFSKfinal.h5\n",
      "WARNING:tensorflow:Layer lstm will not use cuDNN kernel since it doesn't meet the cuDNN kernel criteria. It will use generic GPU kernel as fallback when running on GPU\n",
      "Loading  result/models/DetectNet/128/CPFSKfinal.h5\n",
      "WARNING:tensorflow:Layer lstm_2 will not use cuDNN kernel since it doesn't meet the cuDNN kernel criteria. It will use generic GPU kernel as fallback when running on GPU\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x864 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "_model = 'DetectNet'\n",
    "_sample_length = 128\n",
    "\n",
    "filename = 'pkl_data/'+str(_sample_length)+'.pkl'\n",
    "\n",
    "plt.figure(figsize=[12,12])\n",
    "for mod in _mods:\n",
    "    \n",
    "    if(_sample_length != 1024 and _model == 'DetectNet'):\n",
    "        x, y, snr = radioml_IQ_data(filename,mod_name=mod, _snr= -10, swap_dim=True)\n",
    "    else:\n",
    "        x, y, snr = radioml_IQ_data(filename,mod_name=mod, _snr= -10, swap_dim=False)\n",
    "        \n",
    "    #carrega modelo\n",
    "    best_model_path = 'result/models/'+str(_model)+'/'+str(_sample_length)+'/'+str(mod)+'final.h5'\n",
    "    print(\"Loading \", best_model_path)\n",
    "    model = load_model(best_model_path)\n",
    "    #faz predicao e desencode\n",
    "    y_pred = model.predict(x)\n",
    "    y_column = np.asarray([np.where(r<0.5)[0] for r in y]).reshape(-1)\n",
    "    #gera ROC\n",
    "    false_positive_rate, true_positive_rate, thresholds = roc_curve(y_column, y_pred[:, 0])\n",
    "    roc_auc = auc(false_positive_rate, true_positive_rate)\n",
    "    #print(\"auc: \", roc_auc)\n",
    "    \n",
    "    #plota ROC\n",
    "    plt.plot(false_positive_rate, true_positive_rate, label='{:s} ROC (area = {:.4f})'.format(mod,roc_auc))\n",
    "\n",
    "plt.plot([0, 1], [0, 1], color='red', linestyle='--', label='Random classifier')\n",
    "plt.xlabel('False Positive Rate')\n",
    "plt.ylabel('True Positive Rate')\n",
    "plt.title('ROC {:s} {:d}'.format(_model, _sample_length))\n",
    "plt.legend(loc=\"lower right\")\n",
    "plt.savefig('imagens/ROC_{:s}_{:d}.png'.format(_model, _sample_length))\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Varia número de features"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Loading  result/models/DetectNet/64/QAM16final.h5\n",
      "WARNING:tensorflow:Layer lstm_8 will not use cuDNN kernel since it doesn't meet the cuDNN kernel criteria. It will use generic GPU kernel as fallback when running on GPU\n",
      "Loading  result/models/DetectNet/128/QAM16final.h5\n",
      "WARNING:tensorflow:Layer lstm will not use cuDNN kernel since it doesn't meet the cuDNN kernel criteria. It will use generic GPU kernel as fallback when running on GPU\n",
      "Loading  result/models/DetectNet/256/QAM16final.h5\n",
      "WARNING:tensorflow:Layer lstm_8 will not use cuDNN kernel since it doesn't meet the cuDNN kernel criteria. It will use generic GPU kernel as fallback when running on GPU\n",
      "Loading  result/models/DetectNet/512/QAM16final.h5\n",
      "WARNING:tensorflow:Layer lstm_24 will not use cuDNN kernel since it doesn't meet the cuDNN kernel criteria. It will use generic GPU kernel as fallback when running on GPU\n",
      "Loading  result/models/DetectNet/1024/QAM16final.h5\n",
      "WARNING:tensorflow:Layer lstm will not use cuDNN kernel since it doesn't meet the cuDNN kernel criteria. It will use generic GPU kernel as fallback when running on GPU\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x864 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "_model = 'DetectNet'\n",
    "mod = 'QAM16'\n",
    "\n",
    "plt.figure(figsize=[12,12])\n",
    "for _sample_length in sample_length:\n",
    "    filename = 'pkl_data/'+str(_sample_length)+'.pkl'\n",
    "    if(_sample_length != 1024 and _model == 'DetectNet'):\n",
    "        x, y, snr = radioml_IQ_data(filename,mod_name=mod, _snr= -10, swap_dim=True)\n",
    "    else:\n",
    "        x, y, snr = radioml_IQ_data(filename,mod_name=mod, _snr= -10, swap_dim=False)\n",
    "        \n",
    "    #carrega modelo\n",
    "    best_model_path = 'result/models/'+str(_model)+'/'+str(_sample_length)+'/'+str(mod)+'final.h5'\n",
    "    print(\"Loading \", best_model_path)\n",
    "    model = load_model(best_model_path)\n",
    "    #faz predicao e desencode\n",
    "    y_pred = model.predict(x)\n",
    "    y_column = np.asarray([np.where(r<0.5)[0] for r in y]).reshape(-1)\n",
    "    #gera ROC\n",
    "    false_positive_rate, true_positive_rate, thresholds = roc_curve(y_column, y_pred[:, 0])\n",
    "    roc_auc = auc(false_positive_rate, true_positive_rate)\n",
    "    #print(\"auc: \", roc_auc)\n",
    "    \n",
    "    #plota ROC\n",
    "    plt.plot(false_positive_rate, true_positive_rate, label='{:d} ROC (area = {:.4f})'.format(_sample_length,roc_auc))\n",
    "\n",
    "plt.plot([0, 1], [0, 1], color='red', linestyle='--', label='Random classifier')\n",
    "plt.xlabel('False Positive Rate')\n",
    "plt.ylabel('True Positive Rate')\n",
    "plt.title('ROC {:s} {:s}'.format(_model, mod))\n",
    "plt.legend(loc=\"lower right\")\n",
    "plt.savefig('imagens/ROC_{:s}_{:s}.png'.format(_model, mod))\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Varia modelo"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Loading  result/models/DetectNet/128/QAM16final.h5\n",
      "WARNING:tensorflow:Layer lstm will not use cuDNN kernel since it doesn't meet the cuDNN kernel criteria. It will use generic GPU kernel as fallback when running on GPU\n",
      "Loading  result/models/DNN/128/QAM16final.h5\n",
      "Loading  result/models/CNN/128/QAM16final.h5\n",
      "Loading  result/models/LSTM/128/QAM16final.h5\n",
      "WARNING:tensorflow:Layer lstm_24 will not use cuDNN kernel since it doesn't meet the cuDNN kernel criteria. It will use generic GPU kernel as fallback when running on GPU\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x864 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "mod = 'QAM16'\n",
    "_sample_length = 128\n",
    "\n",
    "filename = 'pkl_data/'+str(_sample_length)+'.pkl'\n",
    "\n",
    "plt.figure(figsize=[12,12])\n",
    "for _model in models:\n",
    "    \n",
    "    if(_sample_length != 1024 and _model == 'DetectNet'):\n",
    "        x, y, snr = radioml_IQ_data(filename,mod_name=mod, _snr= -10, swap_dim=True)\n",
    "    else:\n",
    "        x, y, snr = radioml_IQ_data(filename,mod_name=mod, _snr= -10, swap_dim=False)\n",
    "        \n",
    "    #carrega modelo\n",
    "    best_model_path = 'result/models/'+str(_model)+'/'+str(_sample_length)+'/'+str(mod)+'final.h5'\n",
    "    print(\"Loading \", best_model_path)\n",
    "    model = load_model(best_model_path)\n",
    "    #faz predicao e desencode\n",
    "    y_pred = model.predict(x)\n",
    "    y_column = np.asarray([np.where(r<0.5)[0] for r in y]).reshape(-1)\n",
    "    #gera ROC\n",
    "    false_positive_rate, true_positive_rate, thresholds = roc_curve(y_column, y_pred[:, 0])\n",
    "    roc_auc = auc(false_positive_rate, true_positive_rate)\n",
    "    #print(\"auc: \", roc_auc)\n",
    "    \n",
    "    #plota ROC\n",
    "    plt.plot(false_positive_rate, true_positive_rate, label='{:s} ROC (area = {:.4f})'.format(_model,roc_auc))\n",
    "\n",
    "plt.plot([0, 1], [0, 1], color='red', linestyle='--', label='Random classifier')\n",
    "plt.xlabel('False Positive Rate')\n",
    "plt.ylabel('True Positive Rate')\n",
    "plt.title('ROC {:s} {:d}'.format(mod, _sample_length))\n",
    "plt.legend(loc=\"lower right\")\n",
    "plt.savefig('imagens/ROC_{:s}_{:d}.png'.format(mod, _sample_length))\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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